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Nextflow workflow for handling Structural Variants

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Nextflow run with conda run with docker run with singularity Launch on Nextflow Tower

Introduction

mskcc/sif is a bioinformatics pipeline that calculates the structural variants mutations from a Tumor/Normal Bam pair.

Sif graph

  1. Calculate SV variants (Delly)
  2. Filter SV variants (Delly)
  3. Concat variants (bcftools)
  4. Convert to maf (vcf2maf)
  5. Generate portal file (format_maf)

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

pairId,tumorBam,normalBam,assay,normalType,bedFile
pair_sample,/bam/path/foo_tumor.rg.md.abra.printreads.bam,/bam/path/foo_normal.rg.md.abra.printreads.bam,IMPACT505,MATCHED,NONE

Important

Make sure the bams have an index file associated with it either file.bam.bai or file.bai should work

Now, you can run the pipeline using:

nextflow run main.nf \
   -profile singularity,test_juno \
   --input samplesheet.csv \
   --outdir <OUTDIR>

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

Credits

mskcc/sif was originally written by Nikhil Kumar @nikhil.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.

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